Baltimore , Maryland
June 25, 2023
June 25, 2023
June 28, 2023
Chemical Engineering Division (ChED) Technical Session 3: Work-in-Progress Part 1
Chemical Engineering Division (ChED)
17
10.18260/1-2--44404
https://peer.asee.org/44404
262
Dr. Olatunde Mosobalaje holds a Chemical Engineering Bachelor degree from Ladoke Akintola University of Technology, Ogbomoso. He is an alumnus of the World Bank-funded African University of Science and Technology, Abuja, where he bagged a Petroleum Engineering MS degree in 2011. In 2019, he completed his Petroleum Engineering PhD program at Covenant University, Ota. He has been a faculty member at the Petroleum Engineering Department of Covenant University since February, 2013. In addition to being a registered engineer (COREN R68878), he is also a member of the Nigerian Society of Engineers, NSE (33597) as well as the Society of Petroleum Engineers, SPE (3495171).
In teaching petroleum engineering course modules, Dr. Mosobalaje adopts a balanced blend of analogical reasoning, concept visualization, field application and workflow coding as a pedagogy style. His recent enrolment in and completion of dozens of online courses (MOOC), delivered by world-class universities, has broaden his view of state-of-the-art teaching methods. As a testimonial of his pursuit of excellence in teaching, he recently received an award as the best teacher in the department from the Dean of Engineering, Covenant University.
Currently, Dr. Mosobalaje’s research interest is in petroleum data analytics (PDA) as well as the deployment of machine learning (ML) tools to petroleum engineering applications. In research (and teaching, too), he leverages his proficiencies in open source platforms such as R and Python and associated libraries (ggplot, gstat, dplyr, scipy, numpy, matplotlib etc). In a modest way, his research products have helped to extend the functionality of some existing geostatistical routines. For his efforts, he recently received the Best Paper award in the 2020 International Conference on Applied Informatics, sponsored by Springer and featuring over 100 authours from 17 countries. Dr. Mosobalaje is open to post-doctoral fellowship/internship opportunities, especially in petroleum data analytics as well as engineering education.
Moses Olayemi is a Doctoral Candidate and Bilsland Dissertation Fellow in the School of Engineering Education at Purdue University. His research interests revolve around the professional development of engineering educators in low resource/post conflict settings and the design and contextualization of instruments to measure the impact of educational interventions. Research projects on these topics have and are currently being conducted in Nigeria, South Sudan, Iraq, Jordan, Kenya, and the US. His dissertation focuses on understanding the nuances and affordances of culturally relevant engineering education in Nigeria and the United States using a comparative case
study methodology.
Reservoir simulation is a state-of-the-art tool for reservoir performance prediction and remains an essential part of chemical and petroleum engineering undergraduate and post-graduate curricula. While the science of reservoir simulation is considered well-taught in academic programs, the literature suggests that students are still unaware of the foundational coding processes behind reservoir simulation software packages. Very little teaching attention has been given to the coding of the governing models and solutions to make these software packages, making reservoir simulation appear like a black box to students. Yet, the coding is indisputably the link between the science and the art. This paper stems from an ongoing project called Pedagogical Unboxing of Reservoir Simulation with Python (PURSIM-Py). This paper presents a classroom adaptation of the project at a private University in Nigeria. Using backward design, in this paper, we present an alignment of the proposed course contents, assessment, and pedagogy (CAP) elements of the course. We propose this alignment be implemented in classes either as a stand-alone course or an accompanying lab to help students unbox reservoir simulation.
Mosobalaje, O. O., & Olayemi, M. (2023, June), Work-in-Progress: A Pedagogical Unboxing of Reservoir Simulation with Python — Backward Design of Course Contents, Assessment, and Pedagogy (CAP) Paper presented at 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland. 10.18260/1-2--44404
ASEE holds the copyright on this document. It may be read by the public free of charge. Authors may archive their work on personal websites or in institutional repositories with the following citation: © 2023 American Society for Engineering Education. Other scholars may excerpt or quote from these materials with the same citation. When excerpting or quoting from Conference Proceedings, authors should, in addition to noting the ASEE copyright, list all the original authors and their institutions and name the host city of the conference. - Last updated April 1, 2015